In reinforcement learning, reward is the primary signal guiding behavior. The authors of a new arXiv preprint observe that reward magnitudes are usually held constant throughout training, while their temporal modulation has received little attention.
The paper proposes "reward inflation" as a way to modulate rewards over time, suggesting it could act as a healthy stimulus for RL. The provided abstract cuts off after this proposal, so the exact mechanism and any experimental results are not described in the available text.
Based on the abstract alone, the significance lies in reframing reward schedules as a tunable component rather than a fixed constant. The claims remain at the proposal stage, with no empirical evidence yet presented in the source.